|
|
|
Methods,
Algorithms and Software for Modeling Physical Systems,
Mathematical
Processing and Analysis of Experimental Data
Theme
leaders:
|
S.V. Shmatov
O. Chuluunbaatar
|
Deputies:
|
N.N.
Voytishin
P.V. Zrelov
|
Participating
countries and international organizations:
Armenia,
Belarus, Bulgaria, CERN, China, Egypt, France, Georgia, Italy,
Kazakhstan, Mexico, Mongolia, Russia, Serbia, Slovakia, South Africa,
United Kingdom, USA, Uzbekistan.
The
problem under study and the main purpose of the research:
The
theme is aimed at organizing and providing computational, algorithmic
and software support for the preparation and implementation of
experimental and theoretical research conducted with JINR’s
participation, at elaborating, developing and using computational
methods for modelling complex physical systems studied within the
projects of the JINR Topical Plan. Within the theme, mathematical
methods and software, including those based on machine and deep
learning algorithms using recurrent and convolutional neural
networks, will be developed for modelling physical processes and
experimental facilities, processing and analysing experimental data
in the field of elementary particle physics, nuclear physics,
neutrino physics, radiobiology, etc. Particular attention will be
paid to the creation of systems for the distributed processing and
analysis of experimental data, as well as information and computing
platforms to support research conducted at JINR and other research
centres.
The
main directions of work are mathematical and computational physics to
support JINR’s large research infrastructure projects,
primarily, the NICA flagship project in the fixed target mode (BM@N)
and in the collider mode for relativistic heavy ion collisions (MPD)
and polarized beams (SPD), the Baikal-GVD neutrino telescope.
Cooperation with experiments at the world’s accelerator centres
(CERN, BNL, etc.), experiments in the field of neutrino physics and
astrophysics, radiobiological research programmes will also be
continued. The possibility of using the developed methods and
algorithms within other projects is being considered.
The major
direction in modelling complex physical systems, including the states
of dense nuclear matter and quantum systems, will be the development
of methods, software packages and numerical research based on the
solution of the corresponding systems of nonlinear, spatially
multidimensional integral, integro-differential or differential
equations in partial derivatives with a large number of parameters
characterized by the presence of critical modes, bifurcations and
phase transitions with the complex application of methods of
computational physics, quantum information theory and hybrid
quantum-classical programming methods.
Within
the theme, it is also planned to develop work on the quantum
intelligent control of technological processes and physical
facilities at JINR, as well as quantum computing in quantum chemistry
and physics.
In
addition, the training of specialists in the field of computational
physics and information technology within the IT School will be
continued.
Projects
in the theme:
|
|
|
Name
of the project
|
Project
Leaders
|
Project
code
|
1.
|
Mathematical
methods, algorithms
and software for modeling physical
processes and experimental facilities,
processing and
analyzing experimental data
|
S.V.
Shmatov
Deputies:
A.S.
Ayriyan
N.N. Voytishin
|
06-6-1119-1-2024/2026
|
2.
|
Methods
of computational physics
for the study of complex systems
|
E.V.
Zemlyanaya
O. Chuluunbaatar
Deputies:
Yu.L.
Kalinovsky
A. Khvedelidze
|
06-6-1119-2-2024/2026
|
Projects:
|
|
|
Name
of the project
|
Project
Leaders
|
Status
|
|
Laboratory
(Subdivision)
|
Responsible
from
laboratories
|
1.
|
Mathematical
methods, algorithms
and
software for modeling physical processes and experimental
facilities, processing and analyzing
experimental data
|
S.V.
Shmatov
Deputies:
A.S.
Ayriyan
N.N.
Voytishin
|
|
|
MLIT
|
P.G.
Akishin, E.P. Akishina, A.I. Anikina, E.I. Alexandrov, I.N.
Alexandrov, D.A. Baranov, T.Zh. Bezhanyan, Yu.A. Butenko, J. Busa,
S. Hnatich,
P.V. Goncharov, N.V. Greben, H. Grigorian, O.Yu.
Derenovskaya,
A.V. Didorenko, N.D. Dikusar, V.V. Ivanov,
A.A. Kazakov, A.I. Kazimov, Z.K. Khabaev, A.C.
Konak,
Yu. V. Korsakov, O.L. Kodolova, B.F. Kostenko,
M.A. Mineev,
Zh.Zh. Musulmanbekov, A.V. Nechaevsky, A.N.
Nikitenko,
E.G. Nikonov, D.A. Oleynik, G.A. Ososkov, V.V. Palichik, V.V.
Papoyan,
I.S. Pelevanyuk, A.Sh. Petrosyan, D.V. Podgainy,
D.I. Pryahina, I. Satyshev, K.V. Slizhevsky, A.G. Soloviev, T.M.
Solovjeva, O.I. Streltsova,
Z.K. Tuhliev, Z.A.Sharipov, S.K.
Slepnev, A.V. Uzhinsky, V.V. Uzhinsky, A.V. Yakovlev, V.B.
Zlokazov, M.I. Zuev
|
|
VBLHEP
|
V.
Yu. Aleksakhin, A.A. Aparin, Yu.V. Bespalov, D.V. Budkovski,
A.V.
Bychkov, I.R. Gabdrakhmanov, A.S. Galoyan, K.V. Gertsenberger,
V.M. Golovatyuk, D.K. Dryablov, M.N. Kapishin, V.Yu. Karzhavin,
A.A. Korobitsyn, A.V. Krylov, A.V. Lanev, V.V. Lenivenko,
S.P. Lobastov, S.P. Merts, A.A. Moshkin, A.A. Mudrokh, D.N.
Nikiforov, M. Patsyuk,
O.V. Rogachevsky, V.G. Ryabov, V.V.
Shalaev, S.G. Shulga, I.A. Zhizhin,
V. Zhezher, A.I.
Zinchenko
|
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BLTP
|
D.I.
Kazakov, M.V. Savina, O.V. Teryaev, V.D. Toneev
|
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FLNP
|
M.
Balasoiu, M.-O. Dima, M.-T. Dima, A.I. Ivankov, A.H. Islamov,
Yu.S. Kovalev, A.I Kuklin, Yu.N. Pepelishev, Yu.L. Ryzhikov,
A.V. Rogachev, V.V. Skoy, M.V. Frontasyeva
|
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DLNP
|
V.A.
Bednyakov, I.A. Belolaptikov, I.V. Borina, A.N. Borodin, V. Dik,
I.I. Denisenko, T.V. Elzhov, A.A. Grinyuk, A.V. Guskov, E.V.
Khramov, V.A. Krylov, V.S. Kurbatov, D.V. Naumov, A.E. Pan, D.
Seitova,
A.E. Sirenko, M.N. Sorokovikov, L.G. Tkachev,
B.A. Shaibonov, E. Sholtan, A.C. Zhemchugov, D.Yu. Zvezdov
|
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LRB
|
I.A.
Kolesnikova, Yu.S. Severyukhin, D.M. Utina
|
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UC
|
D.V.
Kamanin, A.Yu. Verkheev, B.S. Yuldashev
|
Brief
annotation and scientific rationale:
The
project is aimed at organizing and providing computational support
for physics research programmes implemented with JINR’s
participation, at developing mathematical methods and software for
modelling physical processes and experimental facilities,
processing and analysing experimental data in the field of
elementary particle physics, nuclear physics, neutrino physics,
condensed matter, radiobiology, etc. The particular attention will
be paid to the creation of systems for the distributed processing
and analysis of experimental data, as well as information and
computing platforms to support research at JINR and other world
centers.
The
main areas of work are mathematical and computational physics to
support JINR’s large research infrastructure projects, first
of all, the experiments at the NICA accelerator complex and the
Baikal-GVD neutrino telescope. Further cooperation with
experiments at the largest world accelerator centers (CERN, BNL,
etc.), experiments in the field of neutrino physics and
astrophysics, radiobiological research programmers will also be
continued. The possibility of using the developed methods and
algorithms within other megascience projects is being considered.
Expected
results upon completion of the project:
Revision
of interaction generators and their development for modelling the
processes of interactions of light and heavy nuclei, including
those at NICA energies (FTF, QGSM, DCM-QGSM-SMM, etc.), and
processes beyond the Standard Model, such as the production of
candidate particles for the role of dark matter, additional Higgs
bosons and processes that violate the lepton number, etc. (QBH,
Pythia, MadGraph, etc.) for LHC conditions at a nominal energy
and a total integrated luminosity up to 450 fb-1.
Development
of algorithms for the reconstruction of charged particle tracks
for experimental facilities, including those at NICA and the LHC,
creation of appropriate software and its application for data
processing and analysis, the study of the physical and technical
characteristics of detector systems.
Development
of scalable algorithms and software for processing
multi-parameter, multi-dimensional, hierarchical data sets of
exabyte volume, including those based on recurrent and
convolutional neural networks, for machine and deep learning
tasks, designed primarily for solving various problems in
particle physics experiments, including for the NICA megaproject
and neutrino experiments.
Creation
and development of data processing and analysis systems and
modern research tools for international collaborations (NICA,
JINR neutrino programme, experiments at the LHC).
Development
of algorithms and software for JINR’s research projects in
the field of neutron physics.
Development
of algorithms, software and computing platforms for
radiobiological research, applied research in the field of proton
therapy and ecology.
Expected
results of the project in the current year:
Revision
of FTF and QGSM models and development of software modules for
modelling nuclear interactions of charmed hadrons, light
hyper-nuclei.
Development
of the DCM-QGSM-SMM generator: considering the dependence of the
lifetime of resonances on the density of the nuclear medium, the
suppression of the production cross section of pseudoscalar
mesons, and the enhancement of the production of hyperons in a
dense nuclear medium, including the deformation of nuclei.
Development
of software for simulating the events indicated in the previous
paragraph, taking into account the performance of the NICA SPD
facility.
Evaluation
of cross sections and modelling of the processes of production of
dark matter particles within extended
two-doublet Higgs
models (MadGraph generator).
Debugging
the procedure for testing sensitive elements of the
high-granularity calorimeter of the CMS experiment, including
track reconstruction and the evaluation of the efficiency of each
detector cell.
Development
and adjustment of algorithms and methods for reconstructing muon
trajectories in the Cathode-Strip Chambers (CSCs) of the muon
system of the CMS experiment for the comparison of the continuous
and discrete approaches of wavelet analysis for separating
overlapping signals; estimation of the CSC spatial resolution and
the aging effect on data obtained in 2024 at the GIF++ facility
at CERN and in proton-proton beam collisions at the LHC.
Optimization
of algorithms for local track reconstruction in the DCH and CSC
detectors of the BM@N experiment, their fitting with
scintillation detectors for global reconstruction and particle
identification, detector alignment and estimation of their
operation parameters with experimental data of 2022–2023.
Finding
and checking correction parameters for the CSC and GEM detectors
of the BM@N experiment, development and implementation of
software for modelling and data processing methods, as well as
their development and adaptation for the current configurations
of a number of GEM and Silicon Profilometer tracking detectors in
2023–2024.
Study
of the effectiveness of the application of machine learning
methods based on decision trees for the particle identification
task in the MPD experiment.
Optimization
of the software platform of the MPD experiment: development and
implementation in MPDRoot on the basic rules of OOP, unified
tests of algorithms and interaction of classes, etc..
Development
and training of a neural network for searching and restoring
tracks in the vertex detector and tracker of the SPD facility,
for restoring clusters in the electromagnetic calorimeter and in
the SPD muon system.
Development
of a data processing and storage model: specification of data
types and formats, estimation of computational costs for
processing at each stage of data transformation, formulation of
technical requirements for a real-time data selection system, a
distributed data processing and storage system, and offline
processing software.
Creation
of a prototype of a system that provides multi-stage data
processing on a real-time event filtering cluster, SPD OnLine
Filter.
Creation
of prototypes of the SPD task management system based on the
PanDA package and the data management system based on the RUCIO
DDM package.
Development
of a prototype system for data processing for the Baikal
telescope.
Development
of a test package for the primary processing of small-angle
experimental data from the YuMO spectrometer for a multi-detector
system with a position-sensitive detector.
Development
of a C++ library for converting online condition data into JSON,
implementation of DCS data conversion to CREST. Modification of
Athena package algorithms using COOL for CREST. Development and
maintenance of the operation of information systems for the BM@N
and MPD experiments to describe the geometry of facilities,
configuration of detectors, management process.
Study
of the background from cosmic protons for the TAIGA observatory,
estimation of the number of evaporation neutrons and
investigation of their interaction in the OLVE-HERO detector.
Analysis
of test data from the prototype of a digital calorimeter for
proton therapy, development of an algorithm based on a cellular
automaton for track recognition and reconstruction.
Application
of piecewise polynomial approximation based on the high-order
basis element method for processing and analysing neutron noise
from the IBR-2M reactor.
Development
of a behavioral analysis module that will automate the analysis
of video data obtained during the testing of laboratory animals
in various test systems.
Application
of algorithms for the automatic selection of optimal data
augmentation policies, testing of various loss minimization
functions, determination of the most effective methods for
classifying images with plant diseases.
Improving
the existing functionality and providing new opportunities for
monitoring and predicting the state of the environment.
Automation of the monitoring process using simulation.
|
2.
|
Methods
of computational physics
for the study of complex systems
|
E.V.
Zemlyanaya
O. Chuluunbaatar
Deputies:
Yu.L.
Kalinovsky
A. Khvedelidze
|
|
|
MLIT
|
V.
Abgaryan, P.G. Akishin, I.V. Amirkhanov, A.S. Ayriyan, E.A.
Ayrjan, D.R. Badreeva, I.V. Barashenkov, M.V. Bashashin, A.A.
Bogolubskaya,
M. Bures, J. Buša, Jr. J. Buša,
Yu.A. Butenko, A.M. Chervyakov,
G. Chuluunbaatar, Kh.
Chuluunbaatar, D. Goderidze, H. Grigorian,
A.A. Gusev,
T.V. Karamysheva, V.V. Kornyak, D.S. Kulyabov,
K.V.
Lukyanov, N.V. Makhaldiani, S.D. Mavlonberdieva, T.I.
Mikhailova, A.V. Nechaevsky, E.G. Nikonov, Yu. Palii , G.V.
Papoyan, V.V, Papoyan, D.V. Podgainy, R.V. Polyakova, T.P.
Puzynina, A.R. Rakhmonova,
V.S. Rikhvitsky, I.A. Rogojin
, B. Saha, I. Sarkhadov, S.I. Serdyukova,
Z.A. Sharipov,
O.I. Streltsova, L.A. Syurakshina, O.V. Tarasov,
A.G.
Torosyan, Z.K. Tukhliev, A.V. Volokhova, O.O. Voskresenskaya,
R.M. Yamaleev, D.A. Yanovich, E.P. Yukalova, O.I.
Yuldashev,
M.B. Yuldasheva, M.I. Zuev
|
|
|
BLTP
|
A.A.
Donkov, A.V. Friesen, M. Hnatic, V.K. Lukyanov, R.G. Nazmitdinov,
I.R., Rahmonov, Yu.M. Shukrinov, S.I. Vinitsky, V.I. Yukalov,
V.Yu. Yushankhai
|
|
FLNR
|
E.
Batchuluun, A.V. Karpov, M.N. Mirzaev, V.V. Samarin, Yu.M. Sereda
|
|
FLNP
|
A.N.
Bugay, A.V. Chizhov
|
|
DLNP
|
O.V.
Karamyshev, G.A. Karamysheva, I.N. Kiyan
|
|
LRB
|
A.N.
Bugay, A.V. Chizhov
|
Brief
annotation and scientific rationale:
The
project is aimed at the development and application of
mathematical and computational methods for modelling complex
physical systems studied within the JINR Topical Plan and
described by systems of dynamic nonlinear, spatially
multidimensional integral, integro-differential or differential
equations that depend on the parameters of models. The evolution
of solutions to such systems can be characterized by the
occurrence of critical modes, bifurcations and phase transitions.
Mathematical modelling is an inseparable part of modern scientific
research. It entails an adequate mathematical formulation of
problems within the models under study, the adaptation of known
numerical approaches or elaboration of new ones to effectively
take into account the features of the studied physical processes,
the development of algorithms and software packages for
high-performance simulation on modern computer systems, including
the resources of the JINR Multifunctional Information and
Computing Complex.
Expected
results upon completion of the project:
Development
of methods, algorithms and software packages for conducting the
numerical research of interactions of various types in complex
systems of nuclear physics and quantum mechanics.
Methods
for modelling multifactorial processes in materials and condensed
matter under external actions.
Methods
for solving simulation tasks in the design of experimental
facilities and the optimization of their operating modes.
Methods
for modelling complex processes in dense nuclear matter based on
the equation of state.
Methods
for modelling quantum systems using quantum information theory
methods and hybrid quantum-classical programming methods.
Expected
results of the project in the current year:
Development
of a mathematical formulation of the problem within the strong
coupling channels method with the Woods–Saxon optical
potential and regular boundary conditions for modelling
sub-barrier heavy ion fusion and fission reactions.
Development
of methods and calculation of the energy of adsorption on the Au
layer of heavy and superheavy atoms.
Development
and optimization of the method of self-similar approximations for
solving nonlinear equations that do not contain small parameters
and describe quantum mechanical systems, including spin ensembles
and cold atoms in traps.
Development
of a method and a programme that initiates, within the
transport-statistical approach, the initial state of colliding
nuclei with nuclear potentials, which are used for further
calculations in collision dynamics.
Modelling
of proton-nucleus interactions, based on a microscopic model of
the optical potential, over a wide range of energies and for a
large variety of atomic numbers of target nuclei with the aim at
assessing the influence of the nuclear medium on the processes of
proton scattering by intranuclear nucleons.
Investigation
of the dynamics of a shock wave in an irradiated material based
on a model described by the combination of molecular dynamic
equations, thermal conductivity equations and wave equations.
Determination of the parameters of the wave equation based on the
results of the numerical solution of molecular dynamics
equations.
Simulation
of the interaction of amyloid beta and antimicrobial peptides
with phospholipid membranes in vesicular and bicellar structures
in the coarse-grained model; study of the dynamic properties of
this interaction based on the calculation of the phonon spectra
of systems; construction of the free energy profile of the
process of pulling the peptide out of the membrane depending on
the distance between the centers of mass and the conformation of
the peptide (replica exchange umbrella sampling).
Study
of localized structures in systems described by nonlinear
damped-driven equations. Investigation of the formation of a
hydrated electron based on a modified polaron model that takes
into account the Coulomb interaction, calculation of the observed
characteristics of this process.
Adaptation
of the COMSOL Multiphysics® package to the HybriLIT
heterogeneous platform in order to enhance the efficiency of
computations and reduce the computational time through the use of
a mixed vector-scalar formulation of magnetostatics and a hybrid
finite and boundary element method. Development and software
implementation of difference schemes for solving a boundary value
problem for a 4th order
equation describing the distribution of physical fields in
2D
and 3D regions of various configurations.
Development
of methods and study of the formation of magnetic fields of
isochronous cyclotrons under various operating modes. Preparation
of instructions and registration of the CORD (Closed ORbit
Dynamics) programme in the JINRLIB library. CORD implements
calculations to study the effect of betatron oscillations and the
phase motion of beam particles on the magnetic field of the
MSC230 cyclotron.
Adaptation
of the neural network approach to the approximate calculation of
multiple integrals arising in the study of pion survival in heavy
ion collisions; elaboration of methods aimed at extending to
finite temperatures the previously developed model of the
quark-hadron phase transition in cold nuclear matter.
Modelling
and calculation of cosmological redshift values based on the
equation of state; investigation of the possibility of
reconstructing the mass spectrum of an isolated neutron star from
the data on the age and surface temperature of pulsars, based on
simulations of their temperature evolution; simulation of the
processes of scattering and production of particles in dense and
hot nuclear matter.
Development
of an evolution operator trotterization algorithm for von Neumann
and Lindblad equations and implementation of the corresponding
quantum circuit on a quantum simulator in the QISKit environment.
Improving the performance of the quantum circuit simulator by
increasing the simulation speed using multiprocessing.
Creation
of a package of modules designed to decompose a quantum system
into subsystems based on the use of the tensor products of
representations of wreath products of finite cyclic groups.
Determination
of the relationship between the characteristics of the
entanglement of composite quantum systems and the negativity of
Wigner quasiprobability distributions. Development of a
functional reduction method for two-loop Feynman integrals and
its application to the calculation of integrals corresponding to
diagrams with four and five external lines.
|
Activities:
|
|
|
Name
of the activity:
|
Leaders
|
Implementation
period
|
|
Laboratory
(Subdivision)
|
Responsible
from
laboratories
|
1.
|
Intelligent
control of technological processes and physical equipment’s
in JINR and quantum computing in quantum chemistry
and
physics
|
P.V.
Zrelov
S.V. Ulyanov
|
2024-2026
|
|
MLIT
|
D.A.
Baranov, O.V. Ivantsova, M.S. Katulin, E.A. Kuznetsov,
A.G.
Reshetnikov, A.R. Ryabov, N.V. Ryabov, L.A. Syurakshina,
D.P.
Zrelova
|
|
VBLHEP
|
Yu.G.
Bespalov, O.I. Brovko, D.N. Nikiforov, G.P. Reshetnikov
|
|
BLTP
|
V.Yu.
Yushankhai
|
Brief
annotation and scientific rationale:
The
main addressed issues of the activity are the development and
effective application of intelligent computing technologies and
the quantum self-organization of inaccurate knowledge in robust
control tasks in order to enhance the reliability of the
functioning of physical facilities. The solution of the tasks is
based on the possibility of increasing the robustness of existing
control systems through embedded knowledge bases. Self-organized
control systems are designed and supported by software tools
developed in the project on the basis of a platform that combines
soft computing and quantum knowledge base optimizers. Embedded
self-organized controllers will be developed for systems of the
intelligent control of JINR’s technological processes,
devices and facilities (including for cases of unforeseen and
unpredictable situations) and intelligent cognitive robotics
tasks.
The
investigation of the effectiveness of quantum algorithms is aimed
at solving the tasks of quantum chemistry and physics of new
functional materials. The application of well-known quantum
algorithms and their development will be carried out on simulators
of classical computing architecture. It is planned to create a
software product for calculating the electronic and magnetic
structures of molecular complexes and crystal fragments of new
functional materials using quantum simulators on classical
computing architectures.
Expected
results upon completion of the activity:
Creation
of a prototype of a quantum fuzzy PID controller and of a
demonstration robot with a built-in controller prototype.
Creation
of a prototype of an intelligent control system for cryogenic
systems of superconducting magnets of the NICA accelerator
complex on the basis of the quantum fuzzy PID controller.
Preparing
a patent.
Methodology
of building and structure of an intelligent control system for a
high-frequency station.
Verification
of the effectiveness of quantum algorithms of variational type
implemented on quantum simulators of classical architecture by
applying them to the quantitative description of the dissociation
of simple molecules, as well as the electronic and spin structure
of the ground state of typical lattice models of quantum theory.
Expected
results of the activity in the current year:
– сreation
of a prototype of a quantum fuzzy PID controller;
– сreation
of the structure of and development of a quantum fuzzy inference
algorithm for a prototype of an intelligent control system for
cryogenic systems of superconducting magnets of the NICA
accelerator complex on the basis of the quantum fuzzy PID
controller.
|
2.
|
Training
of specialists in the field
of computational physics and
information technology
|
V.V.
Korenkov
A.V. Nechaevsky
D.I. Pryahina
O.I.
Streltsova
|
2024-2026
|
|
MLIT
|
T.Zh.
Bezhanyan, O.Yu. Derenovskaya, Е.Mazhitova,
I.S.
Pelevanyuk, A.S. Vorontsov, E.N. Voytishina, M.I. Zuev
|
|
UC
|
D.V.
Kamanin, A.Yu. Verkheev
|
Brief
annotation and scientific rationale:
The
training and retraining of specialists in computational physics
and information technology on the basis of the Multifunctional
Information and Computing Complex (MICC) of the Joint Institute
for Nuclear Research (JINR) and its educational components are
performed for:
– upskilling
JINR staff members in order to develop scientific projects,
including megascience ones, which are implemented at JINR or with
its participation, as well as to create and support the JINR
Digital EcoSystem (DES);
– disseminating
competencies in computational physics and information technology
to the regions of Russia and the JINR Member States to enhance the
personnel potential of JINR and organizations cooperating with the
Institute.
The
main prerequisite for the creation of the activity is the
necessity to form a research environment in order to ensure the
professional growth of IT specialists, the creation and
development of scientific groups, and the engagement of new
specialists in JINR projects. The additional training of the
personnel, mainly on request of the JINR Laboratories, should be
aimed at developing special competencies, in-depth knowledge and
practical skills in computational physics and information
technology.
Expected
results upon completion of the activity:
Holding
events for JINR staff members to study state-of-the-art
information technologies and opportunities to work on the MICC
components and in the DES.
Forming
a set of JINR projects in which students can participate.
Forming
a list of competencies and required courses for the
implementation of projects.
Elaboration
of training courses and educational programmes that will provide
personnel training for solving a variety of tasks within
projects.
Creation
of an ecosystem for the implementation of educational programmes
on the basis of the JINR MICC, including the cloud
infrastructure, the HybriLIT heterogeneous computing platform,
which comprises the education and testing polygon and the
“Govorun” supercomputer.
Creation
of a software and information environment and a platform for
organizing and holding events, lectures, workshops, hackathons,
etc.
Involvement
of specialists from JINR and JINR Information Centres,
researchers from the JINR Member States’ organizations,
lecturers from leading educational organizations that cooperate
with JINR in order to hold educational and scientific events.
Forming
event programmes and organizing interaction with universities and
JINR Information Centres.
Expected
results of the activity in the current year:
1. Holding
events for JINR staff members (seminars for users of the JINR
MICC and the DES).
2.
Creation of an ecosystem component for the implementation of
educational programmes.
3.
Conducting JINR Schools of Information Technologies.
4.
Conducting training practices for students of the Russian
Federation and the JINR Member States.
5.
Elaboration of training courses on information technology.
|
Collaboration
Country
or International Organization
|
City
|
Institute
or laboratory
|
Armenia
|
Yerevan
|
Foundation
ANSL
|
|
|
YSU
|
Belarus
|
Gomel
|
GSU
|
|
Minsk
|
IM
NASB
|
|
|
IP
NASB
|
|
|
INP
BSU
|
Bulgaria
|
Sofia
|
SU
|
CERN
|
Geneva
|
CERN
|
China
|
Beijing
|
CIAE
|
Egypt
|
Cairo
|
ASRT
|
|
Giza
|
CU
|
France
|
Saclay
|
IRFU
|
Georgia
|
Tbilisi
|
GTU
|
|
|
TSU
|
|
|
UG
|
Italy
|
Genoa
|
INFN
|
Kazakhstan
|
Almaty
|
IETP
KazNU
|
|
|
INP
|
|
Astana
|
ENU
|
Mexico
|
Mexico
City
|
UNAM
|
Mongolia
|
Ulaanbaatar
|
IMDT
MAS
|
|
|
MUST
|
Russia
|
Arkhangelsk
|
NArFU
|
|
Dubna
|
Dubna
State Univ.
|
|
Gatchina
|
NRC
KI PNPI
|
|
Irkutsk
|
ISU
|
|
Moscow
|
ITEP
|
|
|
LPI
RAS
|
|
|
MSU
|
|
|
NNRU
“MEPhI”
|
|
|
PFUR
|
|
|
RCC
MSU
|
|
|
RSTSREC
|
|
|
SINP
MSU
|
|
Moscow,
Troitsk
|
INR
RAS
|
|
Petropavlovsk-Kamchatsky
|
KSU
|
|
Protvino
|
IHEP
|
|
Puschino
|
IMPB
RAS
|
|
Samara
|
SSU
|
|
Saratov
|
SSU
|
|
Saint
Petersburg
|
SPbSU
|
|
Tomsk
|
TPU
|
|
Tula
|
TSU
|
|
Tver
|
TvSU
|
|
Vladikavkaz
|
NOSU
|
|
Vladivostok
|
FEFU
|
|
Voronezh
|
VSU
|
Serbia
|
Belgrade
|
Univ.
|
Slovakia
|
Kosice
|
UPJS
|
South
Africa
|
Cape
Town
|
UCT
|
United
Kingdom
|
Oxford
|
Univ.
|
USA
|
Arlington,
TX
|
UTA
|
Uzbekistan
|
Tashkent
|
AS
RUz
|
| |
▲ |
|